Non-invasive imaging techniques are widely used in security screening, quality control, and medical diagnostic systems. Particularly, in medical imaging, non-invasive imaging techniques such as multi-energy imaging allow for unobtrusive, convenient and fast imaging of underlying tissues and organs. To that end, radiographic imaging systems such as nuclear medicine (NM) gamma cameras, computed tomography (CT) systems, single photon emission CT (SPECT) systems and positron emission tomography (PET) systems generate images that illustrate various biological processes and functions for medical diagnoses and treatment.
PET systems, for example, generate images that represent a distribution of positron-emitting nuclides within a patient's body. Typically, a positron-electron interaction results in annihilation, thus converting entire mass of the positron-electron pair into two 511 kilo-electron volt (keV) photons emitted in opposite directions along a line of response (LOR). In a PET system, detectors placed along the LOR on a detector ring detect the annihilation photons. Particularly, the detectors detect a coincidence event if the photons arrive and are detected at the detector elements at the same time. The PET system uses the detected coincidence information along with other acquired image data for generating two-dimensional (2D) or three-dimensional (3D) PET images for further diagnosis and treatment. To that end, the PET systems may use, for example, Fourier-based or model-based image reconstruction techniques.
Specifically, certain clinical applications may entail use of high-fidelity, near real-time 3D images for investigating and accurately characterizing minute features within a pathological region of a patient, such as in and around a human heart. Typically, the quality of the PET images depends on image statistics, which in turn are closely related to detected coincidence events. Furthermore, the total scan time for detecting the coincidence events may be limited, for example, by the decay of a radioactive isotope used in imaging and by the inability of the patients to remain immobile for extended durations. Additionally, patient size, attenuation, physiology, injected dose and spatial distribution of the detected radiation events affect image quality, often resulting in inadequate signal-to-noise ratio (SNR) at the region of interest (ROI).
Accordingly, certain PET scanners may employ time-of-flight (TOF) information corresponding to a measured difference in time between arrivals of each pair of gamma photons from each annihilation event for reconstructing 3D TOF images with high SNR. Fully 3D TOF PET image reconstruction, for example, using accurate system and noise models, however, involves huge data volumes that entail complex computation and long processing times, thus needing specialized hardware and additional costs. Further, the time and complexity involved in conventional fully 3D TOF imaging limit use of the 3D TOF data in real-time clinical environments.
In view of the huge data volumes, certain PET systems employ analytical or iterative image reconstruction techniques such as using ordered subset expectation-maximization (OSEM) algorithms that reduce computation cost but may sacrifice image quality. Certain other systems rebin 3D TOF data into a lower dimensional space such as into 2D TOF data, for example, using Single Slice Rebinning (SSRB-TOF) or Fourier rebinning techniques. Furthermore, some PET systems are known to employ multi-resolution image reconstruction approaches.
Although these rebinning techniques and multi-resolution approaches reduce data size, they may not be sufficient to accelerate the computations for 3D TOF PET reconstructions significantly, especially in real-time clinical environments that require high fidelity and low-latency 3D TOF images.